[논문]Social Determinants of COVID-19 in Massachusetts, United States: An Ecological Study

Hawkins, Devan

doi:10.3961/jpmph.20.256

Social Determinants of COVID-19 in Massachusetts, United States: An Ecological Study 원문보기 논문타임라인

Journal of preventive medicine and public health = 예방의학회지, v.53 no.4, 2020년, pp.220 - 227

Hawkins, Devan (Instructor of Public Health, Public Health Program, School of Arts and Sciences, MCPHS University)

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Objectives: The aim of this study was to assess how different social determinants of health (SDoH) may be related to variability in coronavirus disease 2019 (COVID-19) rates in cities and towns in Massachusetts (MA). Methods: Data about the total number of cases, tests, and rates of COVID-19 as of June 10, 2020 were obtained for cities and towns in MA. The data on COVID-19 were matched with data on various SDoH variables at the city and town level from the American Community Survey. These variables included information about income, poverty, employment, renting, and insurance coverage. We compared COVID-19 rates according to these SDoH variables. Results: There were clear gradients in the rates of COVID-19 according to SDoH variables. Communities with more poverty, lower income, lower insurance coverage, more unemployment, and a higher percentage of the workforce employed in essential services, including healthcare, had higher rates of COVID-19. Most of these differences were not accounted for by different rates of testing in these cities and towns. Conclusions: SDoH variables may explain some of the variability in the risk of COVID-19 across cities and towns in MA. Data about SDoH should be part of the standard surveillance for COVID-19. Efforts should be made to address social factors that may be putting communities at an elevated risk.

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제안 방법

In the final model, because of evidence that the rate of COVID-19 varies according to age [14], we controlled for the median age of the city or town. For the models examining differences in the percentage of positive cases, we constructed 2 models: the first examining only social variables, and the second controlling for median age.
gov/. The specific measures used in this analysis included median income; the percentage of residents who were uninsured, below the poverty line, unemployed, and renters; and percentage of workers employed in the transportation and healthcare and social assistance industries and in service and healthcare support occupations. For each of these measures, cities and towns were categorized into one of four categories according to the quartile of their percentage for the distribution of a given variable.

데이터처리

Table 1 shows the quartile cut-offs that were used for each variable. We also performed Poisson regression with a log-link using SAS version 9.3 (SAS Institute Inc., Cary, NC, USA) to calculate rate ratios comparing the rates and the percentages of positive tests in the quartiles. For rates of COVID-19, we constructed 3 models.

성능/효과

The findings from this study highlight that the burden of COVID-19 in MA is falling most heavily on communities with a number of social vulnerabilities. These findings are suggestive of factors that may be contributing to geographic differences in COVID-19.
The communities with missing ACS data varied considerably in size, ranging from Billerica with a population of 42 664 to Gosnold with a population of 62. These exclusions resulted in a final sample of 87 256 cases of COVID-19 diagnosed in MA through June 10, 2020, representing 87.1% of the total cases diagnosed in MA. The number of cases per 100 000 people for the cities and towns included in the analysis (1584.
In April 2020, MA began publishing data about confirmed cases of COVID-19 and the number of people tested for COVID-19 in cities and towns in MA [13]. This study sought to determine whether variations in the rates and trends in cases ofCOVID-19 and the percentage of positive tests for COVID-19were associated with a variety of social factors including poverty, median income, employment in the health care and transportation industries and healthcare support and service occupations, rented accommodations, unemployment, and lack of insurance.

참고문헌 (27)
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Social Determinants of COVID-19 in Massachusetts, United States: An Ecological Study 원문보기 논문타임라인

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